Perhaps the most famous disclaimer on Wall Street is that “past performance is no guarantee of commensurate future returns.” While popular with the lawyers advising the promoters of mutual funds and the like, the above disclaimer is in fact contrary to an entire body of investment advisory techniques—known as technical analysis. Technical analysts collect large amounts of price data for select securities and graphically display the price v. time relationships for select periods. The resulting charts are then examined with the learned eye of the technical analyst with the hope of recognizing one or more familiar patterns in the recent price data on the chart. Through experience, patterns of price movements have been associated with future price increases (bullish sentiments) or alternatively, price drops (bearish sentiments).
Technical analysis, on one level, is largely an exercise in human interpretation of complex graphics, as the data relating to price movements—say stock in a corporation—is charted in Cartesian coordinates for review. Applying this technique at its most basic level eschews traditional tools of investment analysts such as price-earning ratios, projected revenue growth, and the like. Indeed, the technical analyst—at this basic level—wholly ignores the attributes underlying the asset, focusing instead on the raw price data as a meaningful projector of future price movements.
While many professionals on Wall Street feel uncomfortable about the usefulness of visual patterns in historical price movements as an important projector of short term future price movements, studies reflect its predictive capabilities. Indeed, it is a tool with significant potential for hedging, day-trading, momentum trading, managing mutual funds, risk management, and the like. Coupled with other analytical tools, and traditional investigatory techniques, sophisticated investors are greatly assisted in discerning the type of investment selection to be made—either for themselves or as advisors for others—such as large institutions, pension funds, or mutual fund companies.
Pattern recognition is an important process in a number of fields. For example, forensic evidence relies on pattern recognition for correlating fingerprint samples, handwriting analysis, and face recognition. Sophisticated software has been developed to assist in handwriting recognition and optical character recognition (“OCR”) apply computers to detect and assess patterns for translation into known logical syllogisms.
Returning to Wall Street, recent trends include the application of large computer systems for intensive fundamental analysis in support of select investment strategies. While technical analysis, as discussed above, relies on human recognition of graphical patterns (shapes) in price—time charts, fundamental analysis applies established mathematical techniques—both algebraic and numerical. More grounded in accepted financial engineering principles, fundamental analysis was quickly adopted and branded as scientific, to contrast it from the more ethereal “technical analysts.” This has resulted in a lesser role for technical analysis in investment forecasting and security selection.
It has been, however, established that forms of technical analysis do, in fact, provide meaningful predictions of future price trends. Within the thicket of subjective analysis and buried by the specialized jargon, a potentially powerful investment tool remained essentially unrealized. See, specifically, “Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation” by Andrew W. Lo, Harry Mamaysky, and Jiang Wang, published in The Journal of Finance, Vol. LV, No. 4, August 2000, pp. 1705-1765—the contents of which are incorporated by reference as if restated in full. It was with this understanding of the problems with the prior art that provided the impetus for the present invention.